mrfse.exact | R Documentation |
A penalized likelihood BIC-based to estimate Markovian neighborhoods.
mrfse.exact(a_size, sample, c, max_neigh= ncol(sample) - 1)
a_size |
Size of the alphabet. |
sample |
A integer-valued matrix. Each value must belong range |
c |
The penalization constant. Must be positive. |
max_neigh |
The maximum length of a candidate Markovian neighborhood. Must be
non-negative and less than |
A list filled with estimated Markov neighborhood for each graph vertex
Rodrigo Carvalho
FRONDANA, Iara Moreira. Model selection for discrete Markov random fields on graphs. São Paulo : Instituto de Matemática e Estatística, University of São Paulo, 2016. Doctoral Thesis in Estatística. <doi:10.11606/T.45.2018.tde-02022018-151123> http://www.teses.usp.br/teses/disponiveis/45/45133/tde-02022018-151123/publico/tese_Iara_Frondana.pdf
library(mrfse) a_size = c(0, 1) s = matrix(sample(a_size, size=1000, replace=TRUE), ncol=5) mrfse.exact(length(a_size), s, 1.0)
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